Now
Computer vision fundamentals
Recreating convolutional nets from Andrew Ng’s labs, double-checking the math, and logging every insight before moving on.
Rahul · DL ➜ CV ➜ RL plan
Learning computer vision first after layering DL concepts so RL feels natural.
I’m Rahul, an ML student mapping the DL → CV → RL journey and documenting every win and struggle. Currently learning DL concepts ➜ CV fundamentals ➜ RL exploration. CV mastery is the immediate goal, RL is the next frontier, and this site is my public notebook for that climb.
- ML
- Andrew Ng specialization completed
- DL
- DeepLearning.AI specialization in progress
- CV ➜ RL
- DL concepts → CV fluency → RL leap
Current learning sprint
CV Foundations
Deep dive month: converting convolution math into intuition, shipping reproducible notebooks, and stress-testing vision layers before the RL hop.
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Lab rebuilds
Re-implementing Andrew Ng convolution labs from scratch to make every tensor op muscle memory.
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Math journaling
Documenting gradient visuals & Khan Academy refreshers so future RL derivations feel friendly.
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Rust side quest
Pairing freeCodeCamp Rust lessons with Python prototypes to sharpen systems thinking.
Week 4 · DL Specialization Course 2/5
Massive thanks to The Organic Chemistry Tutor for math clarity and Boris Meinardus for inspiring this whole ML pursuit.
Next
Reinforcement learning jump
Once CV feels natural, I’ll port the intuition to RL—starting with value/policy basics and small Gymnasium environments.
Superpowers
Networks, music, and F1 resets
I’m the go-to troubleshooter for PCs and networks, and I reset by looping Jeremy Zucker playlists or catching every F1 race possible—music (a lot of it) keeps the focus sharp.
About
ML beginner chasing CV & RL mastery
I wrapped Andrew Ng’s Machine Learning specialization, I’m deep into the DeepLearning.AI DL specialization, and I’m rebuilding math intuition through Khan Academy sessions. Python is home base, Rust is my YouTube (freeCodeCamp) side quest, and I’m still the on-call tech support who can fix Wi-Fi or build a PC from parts.
Structured learning
Coursera playlists keep the roadmap steady—Machine Learning specialization ✅, DeepLearning.AI DL specialization currently underway with detailed notes.
Math catch-up
Khan Academy plus The Organic Chemistry Tutor refreshers for linear algebra, calculus, probability, and optimization so derivations feel friendly instead of frightening.
Tools & tinkering
Comfortable in Python notebooks, learning Rust via freeCodeCamp, tweaking networks, and building PCs—basically the go-to fixer for friends and family.
Contact
Reach out, swap notes, or just say hi
Whether you want to nerd out about DL → CV → RL progress, share your favorite Jeremy Zucker track, or debate the latest F1 strategy call, my inbox is open. Email me anytime at rahuldldev81@gmail.com and I’ll swap notes, PC-building tips, or YouTube learnings.
PS: Eternal gratitude to The Organic Chemistry Tutor and Boris Meinardus for lighting the way—this site is my thank-you note.
Bonus: peek at my study playlists on YouTube.
Blog
Learning notes landing soon
The very first post is live! Expect more deep dives on Andrew Ng + DL labs, math refreshers, and CV/RL experiments as I keep publishing.
Taming Fedora 43 on the Lenovo Yoga Pro 7
How I fixed Howdy, Wi-Fi crashes, and Bluetooth on Fedora 43 (Rawhide) running on a Lenovo Yoga Pro 7.
From Vibe Coding to Deep Learning
How I wandered from Hack The Box builds and “vibe coded” tooling to finally respecting ML math, finding Boris Meinardus’ roadmap, and committing to the DL specialization.
More entries are brewing. Want a ping when they drop? Send me a note and I’ll keep you posted.